MobiCom 2016 论文列表

The Location Service (LCS) proposed by the telecommunication industry is an architecture that allows the location of mobile devices to be accessed in various applications. We explore the use of LCS in location-enhanced server authentication, which traditionally relies on certificates. Given recent incidents involving certificate authorities, various techniques to strengthen server authentication were proposed. They focus on improving the certificate validation process, such as pinning, revocation, or multi-path probing. In this paper, we propose using the server's geographic location as a second factor of its authenticity. Our solution, SALVE, achieves location-based server authentication by using secure DNS resolution and by leveraging LCS for location measurements. We develop a TLS extension that enables the client to verify the server's location in addition to its certificate. Successful server authentication therefore requires a valid certificate and the server's presence at a legitimate geographic location, e.g., on the premises of a data center. SALVE prevents server impersonation by remote adversaries with mis-issued certificates or stolen private keys of the legitimate server. We develop a prototype implementation and our evaluation in real-world settings shows that it incurs minimal impact to the average server throughput. Our solution is backward compatible and can be integrated with existing approaches for improving server authentication in TLS.

In this paper, we propose a near-ultrasound chirp signal-based communication for the TV's 2nd screen services. While near-ultrasound (with under 20 kHz frequency) communication has been developed for various applications recently, none of the previous work provides a perfect solution for 2nd screen services between TVs and smart devices. This is due mainly to the following real world challenges. The embedded signal in TV contents should be successfully received in a typical TV-watching environment by (i) delivering information at least at 15 bps with significantly low volume to avoid human perception, (ii) despite the presence of ambient noise, e.g., a tick, a snap, or a knock. To fulfill (i), we design chirp quaternary orthogonal keying (QOK) symbols. Especially, we aim to minimize inter-symbol interference (ISI) effects by symbol design in order to completely eliminate guard intervals. To resolve (ii), we propose the novel J-shape detection algorithms for both frame synchronization and carrier sensing. The proposed modem achieves almost zero frame error rate on a smartphone 2.7 m away from the TV even with minimal receive sound pressure level of 35 dBSPL, i.e., the noise level in a very quiet room. Moreover, throughout experiments and log analysis of 2nd screen service deployed in a nation-wide TV broadcasting system, J-shape detection algorithms are proven to achieve highly resilient performance for both frame synchronization and carrier sensing compared to previous schemes.

In this work, we explore the potential and impact of unlicensed LTE on WiFi in unlicensed spectrum. Our experiments demonstrate that the large asymmetry in the channel access methodologies employed by WiFi and LTE (carrier sensing/notification in WiFi, energy sensing alone in LTE-U), can result LTE-U completely blocking WiFi transmissions, and causing significant degradation to either technologies from collisions.

Device-free localization of people and objects indoors not equipped with radios is playing a critical role in many emerging applications. This paper presents an accurate model-based device-free localization system LiFS, implemented on cheap commercial off-the-shelf (COTS) Wi-Fi devices. Unlike previous COTS device-based work, LiFS is able to localize a target accurately without offline training. The basic idea is simple: channel state information (CSI) is sensitive to a target's location and by modelling the CSI measurements of multiple wireless links as a set of power fading based equations, the target location can be determined. However, due to rich multipath propagation indoors, the received signal strength (RSS) or even the fine-grained CSI can not be easily modelled. We observe that even in a rich multipath environment, not all subcarriers are affected equally by multipath reflections. Our pre-processing scheme tries to identify the subcarriers not affected by multipath. Thus, CSIs on the "clean" subcarriers can be utilized for accurate localization.

Owing to dense deployment of light fixtures and multipath-free propagation, visible light localization technology holds potential to overcome the reliability issue of radio localization. However, existing visible light localization systems require customized light hardware, which increases deployment cost and hinders near term adoption. In this paper, we propose LiTell, a simple and robust localization scheme that employs unmodified fluorescent lights (FLs) as location landmarks and commodity smartphones as light sensors. LiTell builds on the key observation that each FL has an inherent characteristic frequency which can serve as a discriminative feature. It incorporates a set of sampling, signal amplification and camera optimization mechanisms, that enable a smartphone to capture the extremely weak and high frequency ( > 80 kHz) features. We have implemented LiTell as a real-time localization and navigation system on Android. Our experiments demonstrate LiTell's high reliability in discriminating different FLs, and its potential to achieve sub-meter location granularity. Our user study in a multi-storey office building, parking lot and grocery store further validates LiTell as an accurate, robust and ready-to-use indoor localization system.

The 60 GHz wireless technology holds great potential for multi-Gbps communications and high-precision radio sensing. But the lack of an accessible experimental platform has been impeding its progress. In this paper, we overcome the barrier with OpenMili, a reconfigurable 60 GHz radio architecture. OpenMili builds from off-the-shelf FPGA processor, data converters and 60 GHz RF front-end. It employs customized clocking, channelization and interfacing modules, to achieve Gsps sampling bandwidth, Gbps wireless bit-rate, and Gsps sample streaming from/to a PC host. It also incorporates the first programmable, electronically steerable 60 GHz phased-array antenna. OpenMili adopts programming models that ease development, through automatic parallelization inside signal processing blocks, and modular, rate-insensitive interfaces across blocks. It provides common reference designs to bootstrap the development of new network protocols and sensing applications. We verify the effectiveness of OpenMili through benchmark communication/sensing experiments, and showcase its usage by prototyping a pairwise phased-array localization scheme, and a learning-assisted real-time beam adaptation protocol.

With the ever-increasing use of smart devices, recent research endeavors have led to unobtrusive screen-camera communication channel designs, which allow simultaneous screen viewing and hidden screen-camera communication. Such practices, albeit innovative and effective, require well-controlled alignment of camera and screen and obstacle-free access.

Device-free gesture tracking is an enabling HCI mechanism for small wearable devices because fingers are too big to control the GUI elements on such small screens, and it is also an important HCI mechanism for medium-to-large size mobile devices because it allows users to provide input without blocking screen view. In this paper, we propose LLAP, a device-free gesture tracking scheme that can be deployed on existing mobile devices as software, without any hardware modification. We use speakers and microphones that already exist on most mobile devices to perform device-free tracking of a hand/finger. The key idea is to use acoustic phase to get fine-grained movement direction and movement distance measurements. LLAP first extracts the sound signal reflected by the moving hand/finger after removing the background sound signals that are relatively consistent over time. LLAP then measures the phase changes of the sound signals caused by hand/finger movements and then converts the phase changes into the distance of the movement. We implemented and evaluated LLAP using commercial-off-the-shelf mobile phones. For 1-D hand movement and 2-D drawing in the air, LLAP has a tracking accuracy of 3.5 mm and 4.6 mm, respectively. Using gesture traces tracked by LLAP, we can recognize the characters and short words drawn in the air with an accuracy of 92.3% and 91.2%, respectively.

3D orientation tracking is an essential ingredient for many Internet-of-Things applications. Yet existing orientation tracking systems commonly require motion sensors that are only available on battery-powered devices. In this paper, we propose Tagyro, which attaches an array of passive RFID tags as orientation sensors on everyday objects. Tagyro uses a closed-form model to transform the run-time phase offsets between tags into orientation angle. To enable orientation tracking in 3D space, we found the key challenge lies in the imperfect radiation pattern of practical tags, caused by the antenna polarity, non-isotropic emission and electromagnetic coupling, which substantially distort phase measurement. We address these challenges by designing a set of phase sampling and recovery algorithms, which together enable reliable orientation sensing with 3 degrees of freedom. We have implemented a real-time version of Tagyro on a commodity RFID system. Our experiments show that Tagyro can track the 3D orientation of passive objects with a small error of 4°, at a processing rate of 37.7 samples per second.

Services like Google Now on Tap and Bing Snapp enable new user experiences by understanding the semantics of contents that users consume in their apps. These systems send contents of currently displayed app pages to the cloud to identify relevant entities (e.g., a movie) appearing in the current page and show information related to such entities (e.g., local theaters playing the movie). These new experiences come with privacy concerns as they can send sensitive on-screen data (bank details, medical data, etc.) to the cloud. We propose a novel approach that efficiently extracts app content semantics on the device, without exfiltrating user data. Our solution consists of two phases: an offline, user-agnostic, in-cloud phase that automatically annotates apps' UI elements with stable semantics, and a lightweight on-device phase that assigns semantics to captured app contents on the fly, by matching the annotations. With this automatic approach we annotated 100+ food, dining, and music apps, with accuracy over 80%. Our system implementation for Android and Windows Phone---Appstract---incurs minimal runtime overhead. We built eight use cases on the Appstract framework.

This paper demonstrates a new technology that can infer a person's emotions from RF signals reflected off his body. EQ-Radio transmits an RF signal and analyzes its reflections off a person's body to recognize his emotional state (happy, sad, etc.). The key enabler underlying EQ-Radio is a new algorithm for extracting the individual heartbeats from the wireless signal at an accuracy comparable to on-body ECG monitors. The resulting beats are then used to compute emotion-dependent features which feed a machine-learning emotion classifier. We describe the design and implementation of EQ-Radio, and demonstrate through a user study that its emotion recognition accuracy is on par with state-of-the-art emotion recognition systems that require a person to be hooked to an ECG monitor.

To meet the growing demand for wireless data, it is time to move away from the age-old paradigm of prohibiting interfering nodes from transmissions. Instead, through proactive management of interference among multiple colliding packets, we can design high throughput wireless systems. This is well explored in the Information Theory community and there are also a few implementational efforts that have been recently reported. The existing solutions are nontrivial to use in real systems as they require either tight time/frequency synchronization or exchange of data between transmitters prior to the transmissions. These requirements are hard to meet in practice especially for uplink transmissions. This paper proposes BASIC, a lightweight multi-user uplink transmission strategy that does not require tight synchronization or exchange of samples among nodes, which makes it an attractive alternative compared to its counterparts. BASIC exploits receiver diversity by controlling the data rates of the clients. A novel greedy algorithm is proposed for data rate selection. We implement BASIC on a software-defined radio platform. Our experiments on a real testbed show that BASIC outperforms TDMA by 48% in terms of overall throughput. Our trace-driven simulations show up to 4.8x gain in throughput with similar flow fairness.

Video streaming is a prevalent mobile service that drains a significant amount of battery power. While various efforts have been made toward saving both video transfer and display energy, they are independently designed in an ad-hoc way and thereby can cause some non-apparent yet critical performance issues. To fill in this gap, this paper presents a fundamentally new design by jointly considering the end-to-end pipeline from the initial video encoding to the final mobile display. In essence, we shift the classic R-D tradeoff that has governed streaming system designs for decades to a fresh rate-distortion-energy (R-D-E) tradeoff specifically tailored for mobile devices. We present RnB, a video bitrate and display brightness adaptation platform that is standard-compliant, backward compatible, and device-neutral in order to achieve the proposed R-D-E tradeoff. RnB is empowered by some new discovery about the inherent relationship among bitrate, display brightness, and video quality as well as by an control-theoretic formulation to dynamically adapt the bitrate and scale the display brightness. Experimental results based on real-time implementation show that RnB can achieve an average of 19% energy reduction with final video quality comparable to conventional R-D based schemes.

The proliferation of mobile devices has enabled extensive mobile-data supported applications, e.g., exercise and activity recognition and quantification. Typically, these applications need predefined features and are only applicable to predefined activities. In this work, we address the issue of deep understanding of arbitrary activities and semantic searching of any activity over massive mobile sensing data. The challenges stem from the rich dynamics and the wide-spectrum of activities that a human being could perform. We propose a hierarchical activity representation, extract common bases of motion data in an unsupervised manner by leveraging the power of deep neural networks, and propose a universal multi-resolution representation for all activities without prior knowledge. Based on this representation, we design an innovative system Lasagna to manage and search motion data semantically. We implement a prototype system and our comprehensive evaluations show that our system can achieve highly accurate activity classification (with precision 98.9%) and search (with recall almost 100% and precision about 90%) over a diverse set of activities.

Video games, Virtual Reality (VR), Augmented Reality (AR), and Smart appliances (e.g., smart TVs) all call for a new way for users to interact and control them. This paper develops high-preCision Acoustic Tracker (CAT), which aims to replace a traditional mouse and let a user play games, interact with VR/AR headsets, and control smart appliances by moving a smartphone in the air. Achieving high tracking accuracy is essential to provide enjoyable user experience. To this end, we develop a novel system that uses audio signals to achieve mm-level tracking accuracy. It lets multiple speakers transmit inaudible sounds at different frequencies. Based on the received sound, our system continuously estimates the distance and velocity of the mobile with respect to the speakers to continuously track it. At its heart lies a distributed Frequency Modulated Continuous Waveform (FMCW) that can accurately estimate the absolute distance between a transmitter and a receiver that are separate and unsynchronized. We further develop an optimization framework to combine FMCW estimation with Doppler shifts and Inertial Measurement Unit (IMU) measurements to enhance the accuracy, and efficiently solve the optimization problem. We implement two systems: one on a desktop and another on a mobile phone. Our evaluation and user study show that our system achieves high tracking accuracy and ease of use using existing hardware.

Traditional vibration inspection systems, equipped with separated sensing and communication modules, are either very expensive (e.g., hundreds of dollars) and/or suffer from occlusion and narrow field of view (e.g., laser). In this work, we present an RFID-based solution, Tagbeat, to inspect mechanical vibration using COTS RFID tags and readers. Making sense of micro and high-frequency vibration using random and low-frequency readings of tag has been a daunting task, especially challenging for achieving sub-millisecond period accuracy. Our system achieves these three goals by discerning the change pattern of backscatter signal replied from the tag, which is attached on the vibrating surface and displaced by the vibration within a small range. This work introduces three main innovations. First, it shows how one can utilize COTS RFID to sense mechanical vibration and accurately discover its period with a few periods of short and noisy samples. Second, a new digital microscope is designed to amplify the micro-vibration-induced weak signals. Third, Tagbeat introduces compressive reading to inspect high-frequency vibration with relatively low RFID read rate. We implement Tagbeat using a COTS RFID device and evaluate it with a commercial centrifugal machine. Empirical benchmarks with a prototype show that Tagbeat can inspect the vibration period with a mean accuracy of 0.36ms and a relative error rate of 0.03%. We also study three cases to demonstrate how to associate our inspection solution with the specific domain requirements.

We present Proteus, a mobile network service control platform to enable safe and rapid evolution of services in a mobile software defined infrastructure (SDI). Proteus allows for network service and network component functionality to be specified in templates. These templates are used by the Proteus orchestrator to realize and modify service instances based on the specifics of a service creation request and the availability of resources in the mobile SDI and allows for service specific policies to be implemented. We evaluate our Proteus prototype in a realistic mobile networking testbed illustrating its ability to support service evolution.

We present new applications for cryptographic secret handshakes between mobile devices on top of Bluetooth Low-Energy (LE). Secret handshakes enable mutual authentication, with the property that the parties learn nothing about each other unless they have been both issued credentials by a group administrator. This property provides strong privacy guarantees that enable interesting applications. One of them is proximity-based discovery for private communities. We introduce MASHaBLE, a mobile application that enables participants to discover and interact with nearby users if and only if they belong to the same secret community. We use direct peer-to-peer communication over Bluetooth LE, rather than relying on a central server. We discuss the specifics of implementing secret handshakes over Bluetooth LE and present our prototype implementation.

Visible Light Communication (VLC) emerges as a new wireless communication technology with appealing benefits not present in radio communication. However, current VLC designs commonly require LED lights to emit shining light beams, which greatly limits the applicable scenarios of VLC (e.g., in a sunny day when indoor lighting is not needed). It also entails high energy overhead and unpleasant visual experiences for mobile devices to transmit data using VLC. We design and develop DarkLight, a new VLC primitive that allows light-based communication to be sustained even when LEDs emit extremely-low luminance. The key idea is to encode data into ultra-short, imperceptible light pulses. We tackle challenges in circuit designs, data encoding/decoding schemes, and DarkLight networking, to efficiently generate and reliably detect ultra-short light pulses using off-the-shelf, low-cost LEDs and photodiodes. Our DarkLight prototype supports 1.3-m distance with 1.6-Kbps data rate. By loosening up VLC's reliance on visible light beams, DarkLight presents an unconventional direction of VLC design and fundamentally broadens VLC's application scenarios.